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  • WolframAlpha Can Now Do In-depth Analysis of Your Facebook Account

    - by Jason Fitzpatrick
    If you’re a big fan of WolframAlpha’s ability to crunch the numbers on just about anything–and we certainly are–you’ll likely be just as delighted as we were to watch it massage the data from your Facebook account. Find out your most liked, discussed, and shared posts, see your Facebook habits, and other neat trends. I unleashed it on my account this morning, not sure what to expect from the results. Within the results tabulation WolframAlpha provided me with all sorts of neat data break downs. I now know exactly how many days it is to my next birthday, the composition of my aggregate posting habits (how many posts are status updates, links, or photos), the time of day when I do the most posting (and what the composition of those posts is), and my average post length. I also know my most liked post and my most commented on post. It will even crunch the numbers on your network of friends (60.6% of my friends are married, for example). By far one of the more interesting data analysis it does on the friendship data, however, is organizing all your friends into relationship clusters so you can see who in your Facebook network is friends with other people in your Facebook network. The service from WolframAlpha is free: simply visit the WolframAlpha search portal and type in “Facebook report” to start the process. You’ll be prompted to create a WolframAlpha account if you don’t have one and to authorize the WolframAlpha Facebook app to access your data. Your Facebook data is cached to your WolframAlpha account for one hour in order to crunch the numbers and display the results. WolframAlpha HTG Explains: How Windows Uses The Task Scheduler for System Tasks HTG Explains: Why Do Hard Drives Show the Wrong Capacity in Windows? Java is Insecure and Awful, It’s Time to Disable It, and Here’s How

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  • How to Implement Complex Form Data?

    - by SoulBeaver
    I'm supposed to implement a relatively complex form that looks like follows, but has at least four more pages requiring the user to fill in all necessary information for the tracks: This data will need to be sent to the server, which is implemented using Dropwizard. I'm looking for best practices on how to upload and send such a complex form with potentially dozens of songs to the server. The simplest available solution I have seen is a simple multipart/form-data request with the following form schema (Source): Client <html> <body> <h1>File Upload with Jersey</h1> <form action="rest/file/upload" method="post" enctype="multipart/form-data"> <p> Select a file : <input type="file" name="file" size="45" /> </p> <input type="submit" value="Upload It" /> </form> </body> </html> Server @POST @Path("/upload") @Consumes(MediaType.MULTIPART_FORM_DATA) public Response uploadTrack(final FormDataMultiPart multiPart) { List<FormDataBodyPart> artists = multiPart.getFields("artist"); StringBuffer output = new StringBuffer(); for (FormDataBodyPart artist : artists) output.append(artist.getValueAs(String.class)); List<FormDataBodyPart> tracks = multiPart.getFields("track"); for (FormDataBodyPart track : tracks) writeToFile(track.getValueAs(InputStream.class), "Foo"); return Response.status(200).entity(output.toString()).build(); } Then I have also read about file uploads via Ajax or Formdata (Mozilla HttpRequest) which allows for Posts in the formats application/x-www-form-urlencoded, multipart/form-data, or text/plain. I don't know which approach, if any, is best. An ideal solution would be to utilize Jackson to convert a json string into my data objects, but I don't get the impression that this is possible with binary data.

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  • Data that has been deleted in P6, how is it updated in Analytics

    - by Jeffrey McDaniel
    In P6 Reporting Database 2.0 the ETL process looked to the refrdel table in the P6 PMDB to determine which projects were deleted. The refrdel table could not be cleared out between ETL runs or those deletes would be lost. After the ETL process is run the refrdel can be cleared out. It is important to keep any purging of the refrdel in a consistent cycle so the ETL process can pick up these deletes and process them accordingly.  In P6 Reporting Database 2.2 and higher the Extended Schema is used as the data source. In the Extended Schema, deleted data is filtered out by the views. The Extended Schema services will handle any interaction with the refrdel table, this concern with timing refrdel cleanup and ETL runs is not applicable as of this release. In the Extended Schema tables (ex. TaskX) there can still be deleted data present. The Extended Schema views join on the primary PMDB tables (ex. Task) and filter out any deleted data.  Any data that was deleted that remains in the Extended Schema tables can be cleaned out at a designated time by running the clean up procedure as documented in the P6 Extended Schema white paper. This can be run occasionally but is not necessary to run often unless large amounts of data has been deleted.

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  • Business Intelligence (BI) Defined

    CIO.com defines Business Intelligence (BI) as a generic reference to a collection of applications that are used to analyze raw organizational data. Typical BI activities include data mining, online analytical processing, querying and reporting. They further explain that the primary reason why a company would utilize BI is to make their more data accessible. The more accessible data is to the users the faster they can identify ways to reduce business cost, discover new business opportunities, and react quickly to adjust prices based on current supply and demand. One area in which a hospital system could use BI derived from a data warehouse can be seen in the Emergency Room (ER) in regards to the number of doctors and nurse they have working during a full moon for each ER location. In order determine this BI needs to determine a trend in the number of patients seen on a full moon, further more they also need to determine the optimal number of staff members working during a full moon be determining the number of employees to patients ration needed to meet standard patient times and also be the most cost effective for the hospital.  This will allow the hospital system to estimate the number of potential patients they will have on the next full moon and adjust their staff schedules accordingly to ensure that patient care is not affected in any way do the influx or lack of influx of patients during this time while also ensuring that they are only working the minimum number of employees to ensure that they still making a profit. Another area where a hospital system could use BI data regards their orders paced to drug and medical supply companies. BI could define trends in prescriptions given to patients, this information could be used for ordering new supplies and forecasting the amount of medicine each hospital needs to keep on site at a given time. For example, a hospital might want to stock up on materials need to set bones in a cast prior to the summer because their BI indicates that a majority of broken bones occur during the summer due to children being out of school and they have more free time.

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  • Globacom and mCentric Deploy BDA and NoSQL Database to analyze network traffic 40x faster

    - by Jean-Pierre Dijcks
    In a fast evolving market, speed is of the essence. mCentric and Globacom leveraged Big Data Appliance, Oracle NoSQL Database to save over 35,000 Call-Processing minutes daily and analyze network traffic 40x faster.  Here are some highlights from the profile: Why Oracle “Oracle Big Data Appliance works well for very large amounts of structured and unstructured data. It is the most agile events-storage system for our collect-it-now and analyze-it-later set of business requirements. Moreover, choosing a prebuilt solution drastically reduced implementation time. We got the big data benefits without needing to assemble and tune a custom-built system, and without the hidden costs required to maintain a large number of servers in our data center. A single support license covers both the hardware and the integrated software, and we have one central point of contact for support,” said Sanjib Roy, CTO, Globacom. Implementation Process It took only five days for Oracle partner mCentric to deploy Oracle Big Data Appliance, perform the software install and configuration, certification, and resiliency testing. The entire process—from site planning to phase-I, go-live—was executed in just over ten weeks, well ahead of the four months allocated to complete the project. Oracle partner mCentric leveraged Oracle Advanced Customer Support Services’ implementation methodology to ensure configurations are tailored for peak performance, all patches are applied, and software and communications are consistently tested using proven methodologies and best practices. Read the entire profile here.

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  • A Web Service to collect data from local servers every hour

    - by anilerduran
    I'm trying to find a way to collect data from different servers around the world. Here are the details: There is only one single PowerShell script on servers that encrypts data (simple csv file) and sends with preferred method (HTTP/HTTPS Post could be) There is no more control on that servers. Can't install any service, process etc. Just I can configure script to execute every hour. This script also will have encrypted username/password/license key for every server. Script will compress data and send to me with these information. So I need a service (I'm not sure if Web Service is the rigth solution) on the cloud that will help me to: Will get data that is sent from servers using a method. Will authenticate request to recognize sender using license key/username/password and most importantly, Will redirect/send this filecab to my SQL Server on the cloud (Azure). Also it should seperate data according to customer information in license key. So every data for every customer will be stored in dedicated DB/Tables on my SQL All the processes above should be completed automatically. No way for manual steps. Question: A Web Service (SOAP or Restful) is the rigth solution for that?

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  • Should I encrypt data in database?

    - by Tio
    I have a client, for which I'm going to do an Web application about patient care, managing patients, consults, history, calendars, everything about that basically. The problem is that this is sensitive data, patient history and such. The client insists on encrypting the data at the database level, but I think this is going to deteriorate the performance of the web app. ( But maybe I shouldn't be worried about this ) I've read the laws about data protection on health issues ( Portugal ), but isn't very specific about this ( I just questioned them about this, I'm waiting for their response ). I've read the following link, but my question is different, should I encrypt the data in the database, or not. One problem that I foresee in encrypting data, is that I'm going to need a key, this could be the user password, but we all know how user passwords are ( 12345 etc etc ), and generating a key I would have to store it somewhere, this means that the programmer, dba, whatever could have access to it, any thoughts on this? Even adding an random salt to the user password isn't going to solve the problem since I can always access it, and therefore decrypt the data.

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  • What is the best way to store a table in C++

    - by Topo
    I'm programming a decision tree in C++ using a slightly modified version of the C4.5 algorithm. Each node represents an attribute or a column of your data set and it has a children per possible value of the attribute. My problem is how to store the training data set having in mind that I have to use a subset for each node so I need a quick way to only select a subset of rows and columns. The main goal is to do it in the most memory and time efficient possible (in that order of priority). The best way I have thought of is to have an array of arrays (or std::vector), or something like that, and for each node have a list (array, vector, etc) or something with the column,line(probably a tuple) pairs that are valid for that node. I now there should be a better way to do this, any suggestions? UPDATE: What I need is something like this: In the beginning I have this data: Paris 4 5.0 True New York 7 1.3 True Tokio 2 9.1 False Paris 9 6.8 True Tokio 0 8.4 False But for the second node I just need this data: Paris 4 5.0 New York 7 1.3 Paris 9 6.8 And for the third node: Tokio 2 9.1 Tokio 0 8.4 But with a table of millions of records with up to hundreds of columns. What I have in mind is keep all the data in a matrix, and then for each node keep the info of the current columns and rows. Something like this: Paris 4 5.0 True New York 7 1.3 True Tokio 2 9.1 False Paris 9 6.8 True Tokio 0 8.4 False Node 2: columns = [0,1,2] rows = [0,1,3] Node 3: columns = [0,1,2] rows = [2,4] This way on the worst case scenario I just have to waste size_of(int) * (number_of_columns + number_of_rows) * node That is a lot less than having an independent data matrix for each node.

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  • MS Access 2003: Can data disappear from records and how do I test for this and prevent it?

    - by user328960
    Problem and about the database: Data from a record in Access 2003 database has disappeared. This database has 1 backend and 3 frontends, multiple users and is hosted on Citrix. Within this database, we have records of all clients served, ranging in the 1000s. Background info: The form for client data entry is set up with various subforms, including both a "programs enrolled" subform and a "services" subform. A client can be enrolled in multiple programs. Once enrolled in a program, services can be entered for that program area using the services subform. There are multiple fields in the services subform, one of which is a drop-down field allowing you to choose from the programs a client has been enrolled in (the list is updated for that client whenever he is enrolled in a new program). The problem details: For one specific record and one specific program area, the program has disappeared from the "programs enrolled" subform and all of the related services have disappeared from the "services" subform for a period of 3 months of data entry. However, other programs and services for this record did not disappear. Questions: Is the disappearance of data a common Access 2003 problem? Are there tests in place that can be run to see if data is disappearing and catch that data? If so, what are they? If there is specific code involved, what is it? What can be done to prevent the disappearing of data (other than using a different database)?

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  • Change Data Capture or Change Tracking - Same as Traditional Audit Trail Table?

    - by HardCode
    Before I delve into the abyss of Microsoft documentation any deeper, I'd like to know if someone experienced with Change Data Capture and Change Tracking know if one or both of these can be used to replace the traditional ... "Audit trail table copy of the 'real table' (all of the fields of the original table, plus date/time, user ID, and DML action field) inserted into by Triggers" ... setup for a database table audit trail, where the trigger populates the audit trail table (which is all manual work). The MSDN overview documentation explains at a high level what Change Data Capture and Change Tracking are, but it isn't clear enough to me, and doesn't state outright, that these tools can be used to replace the traditional audit trail tables we've made so often. Can someone with any experience using Change Data Capture and Change Tracking save me a lot of time, or confirm that I am spending time looking at the right tool? The critical part of our audit trail is capturing all changes to a table's fields (on INSERT, UPDATE, DELETE), when it happened, and who did it. These changes are commonly provided to an end user chronologically via an audit trail report. Which is another question ... Change Data Capture or Change Tracking is the solution, I'd assume that this data can be queried just like data from a normal table? EDIT: I need a permanent audit trail, irregardless of time. I see that Change Data Capture has to do with the transaction logs, so this sounds finite to me.

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  • Interesting Scala typing solution, doesn't work in 2.7.7?

    - by djc
    I'm trying to build some image algebra code that can work with images (basically a linear pixel buffer + dimensions) that have different types for the pixel. To get this to work, I've defined a parametrized Pixel trait with a few methods that should be able to get used with any Pixel subclass. (For now, I'm only interested in operations that work on the same Pixel type.) Here it is: trait Pixel[T <: Pixel[T]] { def mul(v: Double): T def max(v: T): T def div(v: Double): T def div(v: T): T } Now I define a single Pixel type that has storage based on three doubles (basically RGB 0.0-1.0), I've called it TripleDoublePixel: class TripleDoublePixel(v: Array[Double]) extends Pixel[TripleDoublePixel] { var data: Array[Double] = v def this() = this(Array(0.0, 0.0, 0.0)) def toString(): String = { "(" + data(0) + ", " + data(1) + ", " + data(2) + ")" } def increment(v: TripleDoublePixel) { data(0) += v.data(0) data(1) += v.data(1) data(2) += v.data(2) } def mul(v: Double): TripleDoublePixel = { new TripleDoublePixel(data.map(x => x * v)) } def div(v: Double): TripleDoublePixel = { new TripleDoublePixel(data.map(x => x / v)) } def div(v: TripleDoublePixel): TripleDoublePixel = { var tmp = new Array[Double](3) tmp(0) = data(0) / v.data(0) tmp(1) = data(1) / v.data(1) tmp(2) = data(2) / v.data(2) new TripleDoublePixel(tmp) } def max(v: TripleDoublePixel): TripleDoublePixel = { val lv = data(0) * data(0) + data(1) * data(1) + data(2) * data(2) val vv = v.data(0) * v.data(0) + v.data(1) * v.data(1) + v.data(2) * v.data(2) if (lv > vv) (this) else v } } Now I want to write code to use this, that doesn't have to know what type the pixels are. For example: def idiv[T](a: Image[T], b: Image[T]) { for (i <- 0 until a.data.size) { a.data(i) = a.data(i).div(b.data(i)) } } Unfortunately, this doesn't compile: (fragment of lindet-gen.scala):145: error: value div is not a member of T a.data(i) = a.data(i).div(b.data(i)) I was told in #scala that this worked for someone else, but that was on 2.8. I've tried to get 2.8-rc1 going, but it doesn't compile for me. Is there any way to get this to work in 2.7.7?

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  • PHP : If...Else...Query

    - by Rachel
    I am executing this statement under while (($data=fgetcsv($this->fin,5000,";"))!==FALSE) Now what I want in else loop is to throw exception only for data value which did not satisfy the if condition. Right now am displaying the complete row as I am not sure how to throw exception only for data which does not satisfy the value. Code if ((strtotime($data[11]) &&strtotime($data[12])&&strtotime($data[16]))!==FALSE && ctype_digit($data[0]) && ctype_alnum($data[1]) && ctype_digit($data[2]) && ctype_alnum($data[3]) && ctype_alnum($data[4]) && ctype_alnum($data[5]) && ctype_alnum($data[6]) && ctype_alnum($data[7]) && ctype_alnum($data[8]) && $this->_is_valid($data[9]) && ctype_digit($data[10]) && ctype_digit($data[13]) && $this->_is_valid($data[14])) { //Some Logic } else { throw new Exception ("Data {$data[0], $data[1], $data[2], $data[3], $data[4], $data[5], $data[6], $data[7], $data[8], $data[9], $data[10], $data[11], $data[12], $data[13], $data[14], $data[16]} is not in valid format"); } Guidance would be highly appreciated as to how can I throw exception only for data which did not satisfy the if value.

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  • SQL SERVER – Copy Data from One Table to Another Table – SQL in Sixty Seconds #031 – Video

    - by pinaldave
    Copy data from one table to another table is one of the most requested questions on forums, Facebook and Twitter. The question has come in many formats and there are places I have seen developers are using cursor instead of this direct method. Earlier I have written the similar article a few years ago - SQL SERVER – Insert Data From One Table to Another Table – INSERT INTO SELECT – SELECT INTO TABLE. The article has been very popular and I have received many interesting and constructive comments. However there were two specific comments keep on ending up on my mailbox. 1) SQL Server AdventureWorks Samples Database does not have table I used in the example 2) If there is a video tutorial of the same example. After carefully thinking I decided to build a new set of the scripts for the example which are very similar to the old one as well video tutorial of the same. There was no better place than our SQL in Sixty Second Series to cover this interesting small concept. Let me know what you think of this video. Here is the updated script. -- Method 1 : INSERT INTO SELECT USE AdventureWorks2012 GO ----Create TestTable CREATE TABLE TestTable (FirstName VARCHAR(100), LastName VARCHAR(100)) ----INSERT INTO TestTable using SELECT INSERT INTO TestTable (FirstName, LastName) SELECT FirstName, LastName FROM Person.Person WHERE EmailPromotion = 2 ----Verify that Data in TestTable SELECT FirstName, LastName FROM TestTable ----Clean Up Database DROP TABLE TestTable GO --------------------------------------------------------- --------------------------------------------------------- -- Method 2 : SELECT INTO USE AdventureWorks2012 GO ----Create new table and insert into table using SELECT INSERT SELECT FirstName, LastName INTO TestTable FROM Person.Person WHERE EmailPromotion = 2 ----Verify that Data in TestTable SELECT FirstName, LastName FROM TestTable ----Clean Up Database DROP TABLE TestTable GO Related Tips in SQL in Sixty Seconds: SQL SERVER – Insert Data From One Table to Another Table – INSERT INTO SELECT – SELECT INTO TABLE Powershell – Importing CSV File Into Database – Video SQL SERVER – 2005 – Export Data From SQL Server 2005 to Microsoft Excel Datasheet SQL SERVER – Import CSV File into Database Table Using SSIS SQL SERVER – Import CSV File Into SQL Server Using Bulk Insert – Load Comma Delimited File Into SQL Server SQL SERVER – 2005 – Generate Script with Data from Database – Database Publishing Wizard What would you like to see in the next SQL in Sixty Seconds video? Reference: Pinal Dave (http://blog.sqlauthority.com)   Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Excel

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  • Data Generator Source Adapter

    This component needs little explanation. It generates random integer (DT_I4) and string (DT_WSTR) data and places them in the pipeline. You specify how many columns of each you would like and for any string columns you pass a fixed length value. You then need to specify how many rows in total you require to be generated. This component is used by us to do testing of the pipeline and components downstream. Previously we would have used a script component (as a source) to generate the rows but found ourselves rewriting the code too often so created this component. Screenshots SQL Server 2005 Integration Services SQL Server 2008/2012 Integration Services The component is provided as an MSI file, however to complete the installation, you will have to add the transformation to the Visual Studio toolbox manually. Right-click the toolbox, and select Choose Items.... Select the SSIS Data Flow Items tab, and then check the Data Generator Source from the list. Downloads The Data Generator Source Adapter is available for SQL Server 2005, SQL Server 2008 (includes R2) and SQL Server 2012. Please choose the version to match your SQL Server version, or you can install multiple versions and use them side by side if you have more than one version of SQL Server installed. Data Generator Source Adapter for SQL Server 2005 Data Generator Source Adapter for SQL Server 2008 Data Generator Source Adapter for SQL Server 2012 Version History SQL Server 2012 Version 3.0.0.30 - SQL Server 2012 release. Includes upgrade support for both 2005 and 2008 packages to 2012. (5 Jun 2012) SQL Server 2008 Version 2.0.0.29 - SQL Server 2008 February 2008 CTP. Includes support for upgrade of 2005 packages. Simplified user interface. (4 Mar 2008) Version 2.0.0.27 - SQL Server 2008 November 2007 CTP. String columns will now use the default system code page. Previously string columns always used 1252. (15 Feb 2008) SQL Server 2005 Version 1.1.0.23 - SQL Server 2005 RTM Refresh. SP1 Compatibility Testing. (12 Jun 2006) Version 1.0.0.0 - SQL Server 2005 IDW 16 Sept CTP. Public release. (6 Oct 2005)

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  • Data Governance (Veri Yönetisimi)

    - by Arda Eralp
    Data governance,veri ile ilgili islemler için bir sorumluluklar sistemidir. Bu sistemin temelini ise politikalar, standartlar ve prosedürler olusturur. Sistem politikalar, standartlar ve prosedürler sayesinde verinin ne zaman, hangi sartlar altinda, hangi eylemlerde, hangi yöntemler ile kimler tarafindan kullanilacagina karar verir. Sistemin kurumda basarili bir sekilde islemesi için öncelikle kurumda farkindalik saglanmasi gereklidir. Farkindalik saglandiktan sonra ise kurum governance ve mimari kültürünü benimsemelidir. Ancak bu sartlar altinda sistem basarili bir sekilde isleyebilecektir. Bu sebeplerden dolayidir ki data governance kisa bir süreç degil, aksine kurum varligini sürdürdügü sürece isleyecek olan bir süreçtir. Bu durum bize data governance in bir proje degil bir program oldugunu açiklamaktadir. Programin baslangicinda kurumun ihtiyaçlarinin netlesmesi ve farkindaligin saglanmasi temeldir. Hedef kitle ise, veri ile dogrudan ve ya dolayli olarak iliski içerisinde olan herkesdir. Bu sebeple programin baslangicinda hedef kitleyi içeren ekipler ile toplantilar düzenlenecektir. Bu toplantilar sayesinde hem farkindalik saglanacak hemde ekiplerin ihtiyaçlari birebir ekipler tarafindan aktarilarak netlesecektir. Hedef kitlenin ihtiyaçlari netlestirildikten sonra ise devamli isleyecek olan bu sürecin planlamasi yapilacaktir. Bu sürecin planlanmasinda ihtiyaçlarin önceliklendirilmesi gerekmektedir. Sebebi ise her ekibin ihtiyaçlarinin farkli olabilecegi ve bütün ihtiyaçlara ayni anda karsilik verilemeyebileceginin öngörülmesidir. Bu öngörünün temeli ise ekiplerin ihtiyaçlarinin birbirleriyle olan baglantisidir. Süreç planlamasinda ihtiyaçlarin önceliklendirilmesinin ardindan kurumun büyüklügünün gözönünde bulundurulmasi gerekmedir. Kurumun büyüklügünün önemi ise eger kurum bir bütün olarak ayni anda govern edilemeyecek kadar büyük ise ihtiyaçlari öncelikli olarak bulunan ekipler ile govern edilmesine baslanarak sürecin belirli bir hiz ile bütün kurumda isler hale getirilmesini saglamaktir. Ihtiyaçlar belirlendikten ve ilgili ekipler seçildikten sonra artik programin planlanmasina geçilebilecek. Programin planlama asamasinda öncelikli olarak sürecin asamalarini kontrol edecek ve süreç kurum içerisinde isleyise geçtiginde kontrolü saglayacak olan Data Governance Office in planlanmasidir. Office in planlanmasiyla birlikte süreçteki roller ve bu rollerin sorumluluklari belirlenecektir. Planlama asamasinda Data governance office, roller ve sorumluluklar, güvenlik ve veri saklanan sistemler ele alinacak konulardir. Planlama asamasi tamamlandiginda ise belirlenen ekipler ve ihtiyaçlar dogrultusunda programin isleyis asamasina geçilebilecektir. Isleyis kisminda ekibin ihtiyaçlari dogrultusunda güvenlik konusunda ve veri saklanan sistemler üzerinde çalismalar yapilacaktir. Bu yapilan çalismalar bir süreç olarak dökümante edilecek ve süreç sona erdiginde baska bir ekiple baska bir ihtiyaç dogrultusunda çalisma yapilarak ayni süreç isletilecek ve böylece kurum içesinde ilgili süreçte standartlasma saglanacaktir. Güvenlik konusunda verinin erisim güvenligi ve kullanim güvenligi ele alinacaktir. Veri saklanan sistemler üzerindeki çalismalar ise saklanan sistemlerin program dahilinde belirlenen standartlar ile olusturulmasi ve yönetilmesi saglanacaktir. Isleyis kisminin ardindan ise programin izleme kismina geçilecektir. Bu kisimda artik Data Governance Office olusmus, politikalar, standartlar ve prosedürler belirlenmistir. Ve Data Governance Office çalisanlari rolleri ve sorumluluklari dahilinde programin isleyisini izleyecek ve gerek gördügünde politikalar standartlar ve prosedürler üzerinde degisiklikler yapacaklardir.

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  • SQL 2014 does data the way developers want

    - by Rob Farley
    A post I’ve been meaning to write for a while, good that it fits with this month’s T-SQL Tuesday, hosted by Joey D’Antoni (@jdanton) Ever since I got into databases, I’ve been a fan. I studied Pure Maths at university (as well as Computer Science), and am very comfortable with Set Theory, which undergirds relational database concepts. But I’ve also spent a long time as a developer, and appreciate that that databases don’t exactly fit within the stuff I learned in my first year of uni, particularly the “Algorithms and Data Structures” subject, in which we studied concepts like linked lists. Writing in languages like C, we used pointers to quickly move around data, without a database in sight. Of course, if we had a power failure all this data was lost, as it was only persisted in RAM. Perhaps it’s why I’m a fan of database internals, of indexes, latches, execution plans, and so on – the developer in me wants to be reassured that we’re getting to the data as efficiently as possible. Back when SQL Server 2005 was approaching, one of the big stories was around CLR. Many were saying that T-SQL stored procedures would be a thing of the past because we now had CLR, and that obviously going to be much faster than using the abstracted T-SQL. Around the same time, we were seeing technologies like Linq-to-SQL produce poor T-SQL equivalents, and developers had had a gutful. They wanted to move away from T-SQL, having lost trust in it. I was never one of those developers, because I’d looked under the covers and knew that despite being abstracted, T-SQL was still a good way of getting to data. It worked for me, appealing to both my Set Theory side and my Developer side. CLR hasn’t exactly become the default option for stored procedures, although there are plenty of situations where it can be useful for getting faster performance. SQL Server 2014 is different though, through Hekaton – its In-Memory OLTP environment. When you create a table using Hekaton (that is, a memory-optimized one), the table you create is the kind of thing you’d’ve made as a developer. It creates code in C leveraging structs and pointers and arrays, which it compiles into fast code. When you insert data into it, it creates a new instance of a struct in memory, and adds it to an array. When the insert is committed, a small write is made to the transaction to make sure it’s durable, but none of the locking and latching behaviour that typifies transactional systems is needed. Indexes are done using hashes and using bw-trees (which avoid locking through the use of pointers) and by handling each updates as a delete-and-insert. This is data the way that developers do it when they’re coding for performance – the way I was taught at university before I learned about databases. Being done in C, it compiles to very quick code, and although these tables don’t support every feature that regular SQL tables do, this is still an excellent direction that has been taken. @rob_farley

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  • Strategy for avoiding duplicate object ids for data shared across devices using iCloud

    - by rmaddy
    I have a data intensive iOS app that is not using CoreData nor does it support iCloud synching (yet). All of my objects are created with unique keys. I use a simple long long initialized with the current time. Then as I need a new key I increment the value by 1. This has all worked well for a few years with the app running isolated on a single device. Now I want to add support for automatic data sync across devices using iCloud. As my app is written, there is the possibility that two objects created on two different devices could end up with the same key. I need to avoid this possibility. I'm looking for ideas for solving this issue. I have a few requirements that the solution must meet: 1) The key needs to remain a single integral data type. Converting all existing keys to a compound key or to a string or other type would affect the entire code base and likely result in more bugs than it's worth. 2) The solution can't depend on an Internet connection. A user must be able to run the app and add data even with no Internet connection. The data should still resolve properly later when the data syncs through iCloud once a connection is available. I'll accept one exception to this rule. If no other option is available, I may be open to requiring an Internet connection the first time the app's data is initialized. One idea I have been toying around with in my head is logically splitting the integer key into two parts. The high 4 or 5 bits could be used as some sort of device id while the rest represents the actual key. The fuzzy part is figuring out how to come up with non-conflicting device ids that fit in a few bits. This should be viable since I don't need to deal will millions of devices. I just need to deal with the few devices that would be shared by a given iCloud account. I'm open to suggestions. Thanks.

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  • Data architecture for event log metrics?

    - by elliot42
    My service has a large ongoing number of user events, and we would like to do things like "count occurrence of event type T since date D." We are trying to make two basic decisions: What to store? Storing every event vs. only storing aggregates (Event log style) log every event and count them later, vs. (Time-series style) store a single aggregated "count of event E for date D" for every day Where to store the data In a relational database (particularly MySQL) In a non-relational (NoSQL) database In flat log files (collected centrally over the network via syslog-ng) What is standard practice / where can I read more about comparing the different types of systems? Additional details: The total event stream is large, potentially hundreds of thousands of entries per day But our current need is only to count certain types of events within it We don't necessarily need real-time access to the raw data or aggregation results IMHO, "log all events to files, crawl them at a later time to filter and aggregate the stream" is a pretty standard UNIX Way, but my Rails-y compatriots seem to think that nothing is real unless it's in MySQL.

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  • JGoodies HashMap

    - by JohnMcClane
    Hi, I'm trying to build a chart program using presentation model. Using JGoodies for data binding was relatively easy for simple types like strings or numbers. But I can't figure out how to use it on a hashmap. I'll try to explain how the chart works and what my problem is: A chart consists of DataSeries, a DataSeries consists of DataPoints. I want to have a data model and to be able to use different views on the same model (e.g. bar chart, pie chart,...). Each of them consists of three classes. For example: DataPointModel: holds the data model (value, label, category) DataPointViewModel: extends JGoodies PresentationModel. wraps around DataPointModel and holds view properties like font and color. DataPoint: abstract class, extends JComponent. Different Views must subclass and implement their own ui. Binding and creating the data model was easy, but i don't know how to bind my data series model. package at.onscreen.chart; import java.beans.PropertyChangeListener; import java.beans.PropertyChangeSupport; import java.beans.PropertyVetoException; import java.util.Collection; import java.util.HashMap; import java.util.Iterator; public class DataSeriesModel { public static String PROPERTY_DATAPOINT = "dataPoint"; public static String PROPERTY_DATAPOINTS = "dataPoints"; public static String PROPERTY_LABEL = "label"; public static String PROPERTY_MAXVALUE = "maxValue"; /** * holds the data points */ private HashMap dataPoints; /** * the label for the data series */ private String label; /** * the maximum data point value */ private Double maxValue; /** * the model supports property change notification */ private PropertyChangeSupport propertyChangeSupport; /** * default constructor */ public DataSeriesModel() { this.maxValue = Double.valueOf(0); this.dataPoints = new HashMap(); this.propertyChangeSupport = new PropertyChangeSupport(this); } /** * constructor * @param label - the series label */ public DataSeriesModel(String label) { this.dataPoints = new HashMap(); this.maxValue = Double.valueOf(0); this.label = label; this.propertyChangeSupport = new PropertyChangeSupport(this); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public DataSeriesModel(String label, DataPoint[] dataPoints) { this.dataPoints = new HashMap(); this.propertyChangeSupport = new PropertyChangeSupport(this); this.maxValue = Double.valueOf(0); this.label = label; for (int i = 0; i < dataPoints.length; i++) { this.addDataPoint(dataPoints[i]); } } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public DataSeriesModel(String label, Collection dataPoints) { this.dataPoints = new HashMap(); this.propertyChangeSupport = new PropertyChangeSupport(this); this.maxValue = Double.valueOf(0); this.label = label; for (Iterator it = dataPoints.iterator(); it.hasNext();) { this.addDataPoint(it.next()); } } /** * adds a new data point to the series. if the series contains a data point with same id, it will be replaced by the new one. * @param dataPoint - the data point */ public void addDataPoint(DataPoint dataPoint) { String category = dataPoint.getCategory(); DataPoint oldDataPoint = this.getDataPoint(category); this.dataPoints.put(category, dataPoint); this.setMaxValue(Math.max(this.maxValue, dataPoint.getValue())); this.propertyChangeSupport.firePropertyChange(PROPERTY_DATAPOINT, oldDataPoint, dataPoint); } /** * returns the data point with given id or null if not found * @param uid - the id of the data point * @return the data point or null if there is no such point in the table */ public DataPoint getDataPoint(String category) { return this.dataPoints.get(category); } /** * removes the data point with given id from the series, if present * @param category - the data point to remove */ public void removeDataPoint(String category) { DataPoint dataPoint = this.getDataPoint(category); this.dataPoints.remove(category); if (dataPoint != null) { if (dataPoint.getValue() == this.getMaxValue()) { Double maxValue = Double.valueOf(0); for (Iterator it = this.iterator(); it.hasNext();) { DataPoint itDataPoint = it.next(); maxValue = Math.max(itDataPoint.getValue(), maxValue); } this.setMaxValue(maxValue); } } this.propertyChangeSupport.firePropertyChange(PROPERTY_DATAPOINT, dataPoint, null); } /** * removes all data points from the series * @throws PropertyVetoException */ public void removeAll() { this.setMaxValue(Double.valueOf(0)); this.dataPoints.clear(); this.propertyChangeSupport.firePropertyChange(PROPERTY_DATAPOINTS, this.getDataPoints(), null); } /** * returns the maximum of all data point values * @return the maximum of all data points */ public Double getMaxValue() { return this.maxValue; } /** * sets the max value * @param maxValue - the max value */ protected void setMaxValue(Double maxValue) { Double oldMaxValue = this.getMaxValue(); this.maxValue = maxValue; this.propertyChangeSupport.firePropertyChange(PROPERTY_MAXVALUE, oldMaxValue, maxValue); } /** * returns true if there is a data point with given category * @param category - the data point category * @return true if there is a data point with given category, otherwise false */ public boolean contains(String category) { return this.dataPoints.containsKey(category); } /** * returns the label for the series * @return the label for the series */ public String getLabel() { return this.label; } /** * returns an iterator over the data points * @return an iterator over the data points */ public Iterator iterator() { return this.dataPoints.values().iterator(); } /** * returns a collection of the data points. the collection supports removal, but does not support adding of data points. * @return a collection of data points */ public Collection getDataPoints() { return this.dataPoints.values(); } /** * returns the number of data points in the series * @return the number of data points */ public int getSize() { return this.dataPoints.size(); } /** * adds a PropertyChangeListener * @param listener - the listener */ public void addPropertyChangeListener(PropertyChangeListener listener) { this.propertyChangeSupport.addPropertyChangeListener(listener); } /** * removes a PropertyChangeListener * @param listener - the listener */ public void removePropertyChangeListener(PropertyChangeListener listener) { this.propertyChangeSupport.removePropertyChangeListener(listener); } } package at.onscreen.chart; import java.beans.PropertyVetoException; import java.util.Collection; import java.util.Iterator; import com.jgoodies.binding.PresentationModel; public class DataSeriesViewModel extends PresentationModel { /** * default constructor */ public DataSeriesViewModel() { super(new DataSeriesModel()); } /** * constructor * @param label - the series label */ public DataSeriesViewModel(String label) { super(new DataSeriesModel(label)); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public DataSeriesViewModel(String label, DataPoint[] dataPoints) { super(new DataSeriesModel(label, dataPoints)); } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public DataSeriesViewModel(String label, Collection dataPoints) { super(new DataSeriesModel(label, dataPoints)); } /** * full constructor * @param model - the data series model */ public DataSeriesViewModel(DataSeriesModel model) { super(model); } /** * adds a data point to the series * @param dataPoint - the data point */ public void addDataPoint(DataPoint dataPoint) { this.getBean().addDataPoint(dataPoint); } /** * returns true if there is a data point with given category * @param category - the data point category * @return true if there is a data point with given category, otherwise false */ public boolean contains(String category) { return this.getBean().contains(category); } /** * returns the data point with given id or null if not found * @param uid - the id of the data point * @return the data point or null if there is no such point in the table */ public DataPoint getDataPoint(String category) { return this.getBean().getDataPoint(category); } /** * returns a collection of the data points. the collection supports removal, but does not support adding of data points. * @return a collection of data points */ public Collection getDataPoints() { return this.getBean().getDataPoints(); } /** * returns the label for the series * @return the label for the series */ public String getLabel() { return this.getBean().getLabel(); } /** * sets the max value * @param maxValue - the max value */ public Double getMaxValue() { return this.getBean().getMaxValue(); } /** * returns the number of data points in the series * @return the number of data points */ public int getSize() { return this.getBean().getSize(); } /** * returns an iterator over the data points * @return an iterator over the data points */ public Iterator iterator() { return this.getBean().iterator(); } /** * removes all data points from the series * @throws PropertyVetoException */ public void removeAll() { this.getBean().removeAll(); } /** * removes the data point with given id from the series, if present * @param category - the data point to remove */ public void removeDataPoint(String category) { this.getBean().removeDataPoint(category); } } package at.onscreen.chart; import java.beans.PropertyChangeEvent; import java.beans.PropertyChangeListener; import java.beans.PropertyVetoException; import java.util.Collection; import java.util.Iterator; import javax.swing.JComponent; public abstract class DataSeries extends JComponent implements PropertyChangeListener { /** * the model */ private DataSeriesViewModel model; /** * default constructor */ public DataSeries() { this.model = new DataSeriesViewModel(); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * constructor * @param label - the series label */ public DataSeries(String label) { this.model = new DataSeriesViewModel(label); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public DataSeries(String label, DataPoint[] dataPoints) { this.model = new DataSeriesViewModel(label, dataPoints); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public DataSeries(String label, Collection dataPoints) { this.model = new DataSeriesViewModel(label, dataPoints); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * full constructor * @param model - the model */ public DataSeries(DataSeriesViewModel model) { this.model = model; this.model.addPropertyChangeListener(this); this.createComponents(); } /** * creates, binds and configures UI components. * data point properties can be created here as components or be painted in paintComponent. */ protected abstract void createComponents(); @Override public void propertyChange(PropertyChangeEvent evt) { this.repaint(); } /** * adds a data point to the series * @param dataPoint - the data point */ public void addDataPoint(DataPoint dataPoint) { this.model.addDataPoint(dataPoint); } /** * returns true if there is a data point with given category * @param category - the data point category * @return true if there is a data point with given category, otherwise false */ public boolean contains(String category) { return this.model.contains(category); } /** * returns the data point with given id or null if not found * @param uid - the id of the data point * @return the data point or null if there is no such point in the table */ public DataPoint getDataPoint(String category) { return this.model.getDataPoint(category); } /** * returns a collection of the data points. the collection supports removal, but does not support adding of data points. * @return a collection of data points */ public Collection getDataPoints() { return this.model.getDataPoints(); } /** * returns the label for the series * @return the label for the series */ public String getLabel() { return this.model.getLabel(); } /** * sets the max value * @param maxValue - the max value */ public Double getMaxValue() { return this.model.getMaxValue(); } /** * returns the number of data points in the series * @return the number of data points */ public int getDataPointCount() { return this.model.getSize(); } /** * returns an iterator over the data points * @return an iterator over the data points */ public Iterator iterator() { return this.model.iterator(); } /** * removes all data points from the series * @throws PropertyVetoException */ public void removeAll() { this.model.removeAll(); } /** * removes the data point with given id from the series, if present * @param category - the data point to remove */ public void removeDataPoint(String category) { this.model.removeDataPoint(category); } /** * returns the data series view model * @return - the data series view model */ public DataSeriesViewModel getViewModel() { return this.model; } /** * returns the data series model * @return - the data series model */ public DataSeriesModel getModel() { return this.model.getBean(); } } package at.onscreen.chart.builder; import java.util.Collection; import net.miginfocom.swing.MigLayout; import at.onscreen.chart.DataPoint; import at.onscreen.chart.DataSeries; import at.onscreen.chart.DataSeriesViewModel; public class BuilderDataSeries extends DataSeries { /** * default constructor */ public BuilderDataSeries() { super(); } /** * constructor * @param label - the series label */ public BuilderDataSeries(String label) { super(label); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public BuilderDataSeries(String label, DataPoint[] dataPoints) { super(label, dataPoints); } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public BuilderDataSeries(String label, Collection dataPoints) { super(label, dataPoints); } /** * full constructor * @param model - the model */ public BuilderDataSeries(DataSeriesViewModel model) { super(model); } @Override protected void createComponents() { this.setLayout(new MigLayout()); /* * * I want to add a new BuilderDataPoint for each data point in the model. * I want the BuilderDataPoints to be synchronized with the model. * e.g. when a data point is removed from the model, the BuilderDataPoint shall be removed * from the BuilderDataSeries * */ } } package at.onscreen.chart.builder; import javax.swing.JFormattedTextField; import javax.swing.JTextField; import at.onscreen.chart.DataPoint; import at.onscreen.chart.DataPointModel; import at.onscreen.chart.DataPointViewModel; import at.onscreen.chart.ValueFormat; import com.jgoodies.binding.adapter.BasicComponentFactory; import com.jgoodies.binding.beans.BeanAdapter; public class BuilderDataPoint extends DataPoint { /** * default constructor */ public BuilderDataPoint() { super(); } /** * constructor * @param category - the category */ public BuilderDataPoint(String category) { super(category); } /** * constructor * @param value - the value * @param label - the label * @param category - the category */ public BuilderDataPoint(Double value, String label, String category) { super(value, label, category); } /** * full constructor * @param model - the model */ public BuilderDataPoint(DataPointViewModel model) { super(model); } @Override protected void createComponents() { BeanAdapter beanAdapter = new BeanAdapter(this.getModel(), true); ValueFormat format = new ValueFormat(); JFormattedTextField value = BasicComponentFactory.createFormattedTextField(beanAdapter.getValueModel(DataPointModel.PROPERTY_VALUE), format); this.add(value, "w 80, growx, wrap"); JTextField label = BasicComponentFactory.createTextField(beanAdapter.getValueModel(DataPointModel.PROPERTY_LABEL)); this.add(label, "growx, wrap"); JTextField category = BasicComponentFactory.createTextField(beanAdapter.getValueModel(DataPointModel.PROPERTY_CATEGORY)); this.add(category, "growx, wrap"); } } To sum it up: I need to know how to bind a hash map property to JComponent.components property. JGoodies is in my opinion not very well documented, I spent a long time searching through the internet, but I did not find any solution to my problem. Hope you can help me.

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  • how to make data that download from google-app-engine readable..

    - by zjm1126
    i use this to download all data from my google app: i follow this article: http://code.google.com/intl/en/appengine/docs/python/tools/uploadingdata.html#Creating_Exporter_Classes and download data use this: bulkloader.py --dump --url=http://zjm1126.appspot.com/remote_api --filename=b.csv but the data is : so how to make the data readable ? thanks

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  • Specifying column names from a list in the data.frame command.

    - by MW Frost
    I have a list called cols with column names in it: cols <- c('Column1','Column2','Column3') I'd like to reproduce this command, but with a call to the list: data.frame(Column1=rnorm(10)) Here's what happens when I try it: > data.frame(cols[1]=rnorm(10)) Error: unexpected '=' in "data.frame(I(cols[1])=" The same thing happens if I wrap cols[1] in I() or eval(). How can I feed that item from the vector into the data.frame() command?

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  • How do i make form data not disappear after hitting refresh?

    - by acidzombie24
    I went to test my page on another browser. On google chrome i can fill out a form, hit back and forward and still have the data there. Now i need to refresh the page so certain data is correct (such as session id if the cookie expires or user logs out before submitting). I refresh and lose all data. Is there some option i can set so all data is kept?

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  • FairWarning Privacy Monitoring Solutions Rely on MySQL to Secure Patient Data

    - by Rebecca Hansen
    FairWarning® solutions have audited well over 120 billion events, each of which was processed and stored in a MySQL database. FairWarning is the world's leading supplier of privacy monitoring solutions for electronic health records, relied on by over 1,200 Hospitals and 5,000 Clinics to keep their patients' data safe. In January 2014, FairWarning was awarded the highest commendation in healthcare IT as the first ever Category Leader for Patient Privacy Monitoring in the "2013 Best in KLAS: Software & Services" report[1]. FairWarning has used MySQL as their solutions’ database from their start in 2005 to worldwide expansion and market leadership. FairWarning recently migrated their solutions from MyISAM to InnoDB and updated from MySQL 5.5 to 5.6. Following are some of benefits they’ve had as a result of those changes and reasons for their continued reliance on MySQL (from FairWarning MySQL Case Study). Scalability to Handle Terabytes of Data FairWarning's customers have a lot of data: On average, FairWarning customers receive over 700,000 events to be processed daily. Over 25% of their customers receive over 30 million events per day, which equates to over 1 billion events and nearly one terabyte (TB) of new data each month. Databases range in size from a few hundred GBs to 10+ TBs for enterprise deployments (data are rolled off after 13 months). Low or Zero Admin = Few DBAs "MySQL has not required a lot of administration. After it's been tuned, configured, and optimized for size on initial setup, we have very low administrative costs. I can scale and add more customers without adding DBAs. This has had a big, positive impact on our business.” - Chris Arnold, FairWarning Vice President of Product Management and Engineering. Performance Schema  As the size of FairWarning's customers has increased, so have their tables and data volumes. MySQL 5.6’ new maintenance and management features have helped FairWarning keep up. In particular, MySQL 5.6 performance schema’s low-level metrics have provided critical insight into how the system is performing and why. Support for Mutli-CPU Threads MySQL 5.6' support for multiple concurrent CPU threads, and FairWarning's custom data loader allow multiple files to load into a single table simultaneously vs. one at a time. As a result, their data load time has been reduced by 500%. MySQL Enterprise Hot Backup Because hospitals and clinics never stop, FairWarning solutions can’t either. FairWarning changed from using mysqldump to MySQL Enterprise Hot Backup, which has reduced downtime, restore time, and storage requirements. For many of their larger customers, restore time has decreased by 80%. MySQL Enterprise Edition and Product Roadmap Provide Complete Solution "MySQL's product roadmap fully addresses our needs. We like the fact that MySQL Enterprise Edition has everything included; there's no need to purchase separate modules."  - Chris Arnold Learn More>> FairWarning MySQL Case Study Why MySQL 5.6 is an Even Better Embedded Database for Your Products presentation Updating Your Products to MySQL 5.6, Best Practices for OEMs on-demand webinar (audio and / or slides + Q&A transcript) MyISAM to InnoDB – Why and How on-demand webinar (same stuff) Top 10 Reasons to Use MySQL as an Embedded Database white paper [1] 2013 Best in KLAS: Software & Services report, January, 2014. © 2014 KLAS Enterprises, LLC. All rights reserved.

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  • Indexing data from multiple tables with Oracle Text

    - by Roger Ford
    It's well known that Oracle Text indexes perform best when all the data to be indexed is combined into a single index. The query select * from mytable where contains (title, 'dog') 0 or contains (body, 'cat') 0 will tend to perform much worse than select * from mytable where contains (text, 'dog WITHIN title OR cat WITHIN body') 0 For this reason, Oracle Text provides the MULTI_COLUMN_DATASTORE which will combine data from multiple columns into a single index. Effectively, it constructs a "virtual document" at indexing time, which might look something like: <title>the big dog</title> <body>the ginger cat smiles</body> This virtual document can be indexed using either AUTO_SECTION_GROUP, or by explicitly defining sections for title and body, allowing the query as expressed above. Note that we've used a column called "text" - this might have been a dummy column added to the table simply to allow us to create an index on it - or we could created the index on either of the "real" columns - title or body. It should be noted that MULTI_COLUMN_DATASTORE doesn't automatically handle updates to columns used by it - if you create the index on the column text, but specify that columns title and body are to be indexed, you will need to arrange triggers such that the text column is updated whenever title or body are altered. That works fine for single tables. But what if we actually want to combine data from multiple tables? In that case there are two approaches which work well: Create a real table which contains a summary of the information, and create the index on that using the MULTI_COLUMN_DATASTORE. This is simple, and effective, but it does use a lot of disk space as the information to be indexed has to be duplicated. Create our own "virtual" documents using the USER_DATASTORE. The user datastore allows us to specify a PL/SQL procedure which will be used to fetch the data to be indexed, returned in a CLOB, or occasionally in a BLOB or VARCHAR2. This PL/SQL procedure is called once for each row in the table to be indexed, and is passed the ROWID value of the current row being indexed. The actual contents of the procedure is entirely up to the owner, but it is normal to fetch data from one or more columns from database tables. In both cases, we still need to take care of updates - making sure that we have all the triggers necessary to update the indexed column (and, in case 1, the summary table) whenever any of the data to be indexed gets changed. I've written full examples of both these techniques, as SQL scripts to be run in the SQL*Plus tool. You will need to run them as a user who has CTXAPP role and CREATE DIRECTORY privilege. Part of the data to be indexed is a Microsoft Word file called "1.doc". You should create this file in Word, preferably containing the single line of text: "test document". This file can be saved anywhere, but the SQL scripts need to be changed so that the "create or replace directory" command refers to the right location. In the example, I've used C:\doc. multi_table_indexing_1.sql : creates a summary table containing all the data, and uses multi_column_datastore Download link / View in browser multi_table_indexing_2.sql : creates "virtual" documents using a procedure as a user_datastore Download link / View in browser

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  • Oracle MDM Maturity Model

    - by David Butler
    A few weeks ago, I discussed the results of a survey conducted by Oracle’s Insight team. The survey was based on the data management maturity model that the Oracle Insight team has developed over the years as they analyzed customer IT organizations to help them get more out of everything they already have. I thought you might like to learn more about the maturity model itself. It can help you figure out where you stand when it comes to getting your organizations data management act together. The model covers maturity levels around five key areas: Profiling data sources; Defining a data strategy; Defining a data consolidation plan; Data maintenance; and Data utilization. Profile data sources: Profiling data sources involves taking an inventory of all data sources from across your IT landscape. Then evaluate the quality of the data in each source system. This enables the scoping of what data to collect into an MDM hub and what rules are needed to insure data harmonization across systems. Define data strategy: A data strategy requires an understanding of the data usage. Given data usage, various data governance requirements need to be developed. This includes data controls and security rules as well as data structure and usage policies. Define data consolidation strategy: Consolidation requires defining your operational data model. How integration is to be accomplished. Cross referencing common data attributes from multiple systems is needed. Synchronization policies also need to be developed. Data maintenance: The desired standardization needs to be defined, including what constitutes a ‘match’ once the data has been standardized. Cleansing rules are a part of this methodology. Data quality monitoring requirements also need to be defined. Utilize the data: What data gets published, and who consumes the data must be determined. How to get the right data to the right place in the right format given its intended use must be understood. Validating the data and insuring security rules are in place and enforced are crucial aspects for full no-risk data utilization. For each of the above data management areas, a maturity level needs to be assessed. Where your organization wants to be should also be identified using the same maturity levels. This results in a sound gap analysis your organization can use to create action plans to achieve the ultimate goals. Marginal is the lowest level. It is characterized by manually maintaining trusted sources; lacking or inconsistent, silo’d structures with limited integration, and gaps in automation. Stable is the next leg up the MDM maturity staircase. It is characterized by tactical MDM implementations that are limited in scope and target a specific division.  It includes limited data stewardship capabilities as well. Best Practice is a serious MDM maturity level characterized by process automation improvements. The scope is enterprise wide. It is a business solution that provides a single version of the truth, with closed-loop data quality capabilities. It is typically driven by an enterprise architecture group with both business and IT representation.   Transformational is the highest MDM maturity level. At this level, MDM is quantitatively managed. It is integrated with Business Intelligence, SOA, and BPM. MDM is leveraged in business process orchestration. Take an inventory using this MDM Maturity Model and see where you are in your journey to full MDM maturity with all the business benefits that accrue to organizations who have mastered their data for the benefit of all operational applications, business processes, and analytical systems. To learn more, Trevor Naidoo and I have written the Oracle MDM Maturity Model whitepaper. It’s free, so go ahead and download it and use it as you see fit.

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